The effects of coagulation factors on the risk of endometriosis: a Mendelian randomization study

Li Y, Yan Li, Hongyan Liu, Shuting Ye, Bumei Zhang, Xiaopei Li, Jiapei Yuan, Yongrui Du, Jianmei Wang, Yang Yang
BMC medicine · 2023 · vol. 21(1) , pp. 195 · doi:10.1186/s12916-023-02881-z · PMID:37226166 · W4377965590
review OA: gold CC0 ⤵ 60 in-corpus citations
📄 Open PDF Full text JSON View on OpenAlex View on PubMed View at publisher
⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This Mendelian randomization study found that genetically predicted plasma ADAMTS13 levels may decrease endometriosis risk, while vWF levels may increase it.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

⚙ AI-generated deep summary by claude@2026-06, 2026-06-08 · read from full text ⓘ

This Mendelian randomization study used publicly available GWAS summary statistics to test whether genetically predicted levels of 11 coagulation factors (including ADAMTS13 and von Willebrand factor) have causal effects on endometriosis risk, using two European-ancestry cohorts (UK Biobank and FinnGen) with separate two-sample MR analyses and meta-analysis. In UK Biobank, genetically predicted plasma ADAMTS13 was associated with decreased endometriosis risk, while FinnGen showed a negative causal effect of ADAMTS13 and a positive causal effect of vWF; MR-Egger intercept, Cochran’s Q, and leave-one-out analyses were used to assess heterogeneity, horizontal pleiotropy, and stability. The paper also reports that these factors showed potential causal effects across endometriosis sub-phenotypes (by anatomic site). This paper is centrally about endometriosis—specifically, causal links between coagulation factors (ADAMTS13 and vWF) and endometriosis risk using Mendelian randomization.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

BACKGROUND: Endometriosis is recognized as a complex gynecological disorder that can cause severe pain and infertility, affecting 6-10% of all reproductive-aged women. Endometriosis is a condition in which endometrial tissue, which normally lines the inside of the uterus, deposits in other tissues. The etiology and pathogenesis of endometriosis remain ambiguous. Despite debates, it is generally agreed that endometriosis is a chronic inflammatory disease, and patients with endometriosis appear to be in a hypercoagulable state. The coagulation system plays important roles in hemostasis and inflammatory responses. Therefore, the purpose of this study is to use publicly available GWAS summary statistics to examine the causal relationship between coagulation factors and the risk of endometriosis. METHODS: To investigate the causal relationship between coagulation factors and the risk of endometriosis, a two-sample Mendelian randomization (MR) analytic framework was used. A series of quality control procedures were followed in order to select eligible instrumental variables that were strongly associated with the exposures (vWF, ADAMTS13, aPTT, FVIII, FXI, FVII, FX, ETP, PAI-1, protein C, and plasmin). Two independent cohorts of European ancestry with endometriosis GWAS summary statistics were used: UK Biobank (4354 cases and 217,500 controls) and FinnGen (8288 cases and 68,969 controls). We conducted MR analyses separately in the UK Biobank and FinnGen, followed by a meta-analysis. The Cochran's Q test, MR-Egger intercept test, and leave-one-out sensitivity analyses were used to assess the heterogeneities, horizontal pleiotropy, and stabilities of SNPs in endometriosis. RESULTS: Our two-sample MR analysis of 11 coagulation factors in the UK Biobank suggested a reliable causal effect of genetically predicted plasma ADAMTS13 level on decreased endometriosis risk. A negative causal effect of ADAMTS13 and a positive causal effect of vWF on endometriosis were observed in the FinnGen. In the meta-analysis, the causal associations remained significant with a strong effect size. The MR analyses also identified potential causal effects of ADAMTS13 and vWF on different sub-phenotypes of endometrioses. CONCLUSIONS: Our MR analysis based on GWAS data from large-scale population studies demonstrated the causal associations between ADAMTS13/vWF and the risk of endometriosis. These findings suggest that these coagulation factors are involved in the development of endometriosis and may represent potential therapeutic targets for the management of this complex disease.
Full text 62,429 characters · extracted from oa-pdf · 19 sections · click to expand

Abstract

Background Endometriosis is recognized as a complex gynecological disorder that can cause severe pain and infertility, affecting 6–10% of all reproductive-aged women. Endometriosis is a condition in which endometrial tissue, which normally lines the inside of the uterus, deposits in other tissues. The etiology and pathogenesis of endometrio- sis remain ambiguous. Despite debates, it is generally agreed that endometriosis is a chronic inflammatory disease, and patients with endometriosis appear to be in a hypercoagulable state. The coagulation system plays important roles in hemostasis and inflammatory responses. Therefore, the purpose of this study is to use publicly available GWAS summary statistics to examine the causal relationship between coagulation factors and the risk of endometriosis.

Methods

To investigate the causal relationship between coagulation factors and the risk of endometriosis, a two- sample Mendelian randomization (MR) analytic framework was used. A series of quality control procedures were followed in order to select eligible instrumental variables that were strongly associated with the exposures (vWF, ADAMTS13, aPTT, FVIII, FXI, FVII, FX, ETP , PAI-1, protein C, and plasmin). Two independent cohorts of European ancestry with endometriosis GWAS summary statistics were used: UK Biobank (4354 cases and 217,500 controls) and FinnGen (8288 cases and 68,969 controls). We conducted MR analyses separately in the UK Biobank and FinnGen, followed by a meta-analysis. The Cochran’s Q test, MR-Egger intercept test, and leave-one-out sensitivity analyses were used to assess the heterogeneities, horizontal pleiotropy, and stabilities of SNPs in endometriosis.

Results

Our two-sample MR analysis of 11 coagulation factors in the UK Biobank suggested a reliable causal effect of genetically predicted plasma ADAMTS13 level on decreased endometriosis risk. A negative causal effect of ADAMTS13 and a positive causal effect of vWF on endometriosis were observed in the FinnGen. In the meta-analysis, the causal associations remained significant with a strong effect size. The MR analyses also identified potential causal effects of ADAMTS13 and vWF on different sub-phenotypes of endometrioses.

Conclusions

Our MR analysis based on GWAS data from large-scale population studies demonstrated the causal associations between ADAMTS13/vWF and the risk of endometriosis. These findings suggest that these coagulation †Yan Li and Hongyan Liu contributed equally to this work. *Correspondence: Jianmei Wang [email protected] Yang Yang [email protected] Full list of author information is available at the end of the article Page 2 of 13Li et al. BMC Medicine (2023) 21:195 factors are involved in the development of endometriosis and may represent potential therapeutic targets for the management of this complex disease.

Keywords

Two-sample Mendelian randomization, Endometriosis, Coagulation, GWAS, ADAMTS13

Background

Endometriosis is defined as the deposit and growth of endometrial tissue that normally lines the inside of the uterus outside the uterine cavity [1]. Women who have endometriosis are more likely to experience dysmen - orrhea, pelvic pain, and even infertility or difficulty conceiving. Endometriosis is a common and complex disorder that affects up to 6–10% of all reproductive-aged women [2]. Although many factors, including hormones, inflammation, genetic factors, epigenetic factors, and environmental factors, are thought to contribute to the development of endometriosis, the etiology and patho - genesis of endometriosis have not been completely elu - cidated [3, 4]. Among the hypotheses that have been proposed to explain the pathogenesis of endometriosis, retrograde menstruation, also known as Sampson’s theory, is the most widely accepted [4, 5]. According to the model of retrograde menstruation, endometrial tissues are shed through the fallopian tubes into the pelvic cavity during menstruation, resulting in the formation of ectopic endo- metriotic lesions on the peritoneal tissue or pelvic organs. The ectopic debris could be cleared by the immune sys - tem in healthy women, whereas the refluxed endometrial fragments might evade the immune surveillance system in endometriosis patients [6–8]. Defective immune sur - veillance is thought to play a role in the implantation and growth of ectopic endometrial tissue [6]. Endometrio - sis is also considered as a chronic inflammatory disease, owing to the presence of ectopic endometrial fragments, which cause an increase in proinflammatory factors and chemotactic cytokines [9–11]. Furthermore, angiogenesis is required to replenish the supply of nutrients and oxy - gen for the growth and survival of endometriotic lesions [12, 13]. Coagulation cascades have been implicated in both inflammatory responses and angiogenesis [12, 14– 16]. Several epidemiological observational studies have found that patients with endometriosis are hypercoagu - lable and hyperfibrinolytic [17, 18]. Plasma fibrinogen, d-dimer, and plasminogen activator inhibitor levels are higher in women with endometriosis when compared to healthy controls while thrombin time and activated par - tial thromboplastin time decrease [19]. Adenomyosis, a condition characterized by endometrial tissue growth within the uterine musculature, shares numerous com - mon symptoms with endometriosis, including pelvic pain and heavy menstrual bleeding [20]. Harmsen et al. have reported the increased levels of von Willebrand factor in ectopic endometrium of adenomyosis patients which are associated with the role of angiogenesis in adenomyosis [21]. Although several observational studies have been conducted to explore the relationship between coagula - tion cascades and endometriosis, the causal associations between coagulation factors and endometriosis remain unclear. The presence of residual confounding and poten- tial reverse causality issues in conventional observational studies poses significant challenges in accurately measur- ing the causal effect of specific coagulation factor on the risk of endometriosis. Residual confounding occurs as a

Result

of inadequate adjustment for confounding varia - bles, as measuring a confounder may not fully character - ize it. In addition, the association between the exposure and outcome may occur due to reverse causality, a phe - nomenon in which the outcome precedes and causes the exposure, rather than the exposure causing the outcome. As an emerging method, Mendelian randomization (MR) is a novel statistical method that examines the causal relationship between the exposure and outcome by using genetic variants as instrumental variables for the exposure of interest [22, 23]. Because genetic variants are randomly allocated during gamete formation and conception, MR analysis could reduce confounding bias and reverse causality [23]. A two-sample MR analysis was carried out in this study to investigate the causal effects of coagulation factors on endometriosis. There were 11 coagulation factors incorporated as the exposures, including vWF (von Willebrand factor), ADAMTS13 (A disintegrin and metalloproteinase with thrombospondin motifs 13), aPTT (activated partial thromboplastin time), FVIII (factor VIII), FXI (factor XI), FVII (factor VII), FX (factor X), ETP (endogenous thrombin potential), PAI-1 (plasminogen activator inhibitor-1), protein C, and plas - min. We leveraged summary-level GWAS data from two independent large-scale cohorts of European ancestry, including the UK Biobank and FinnGen cohorts, to esti - mate a putative causal association of a specific coagula - tion factor with the risk of endometriosis.

Methods

Study design Three critical assumptions must be met in the MR anal - ysis. The first assumption is that the genetic variables should be significantly related to the exposure, the sec - ond assumption is that genetic variants extracted as Page 3 of 13 Li et al. BMC Medicine (2023) 21:195 instrumental variables for the exposure are not related to other confounding factors, and the third assump - tion is that genetic variants influence the outcome solely through their effects on the exposure (i.e., no horizontal pleiotropic effect) [24]. Figure 1 depicts the overall design of this study. We began by selecting 11 coagulation fac - tors based on publicly available GWAS data. Based on the GWAS summary statistics, we selected instrumental var - iables for each coagulation factor. Then, using summary- level GWAS data of endometriosis from two independent cohorts, including the UK Biobank and FinnGen, we con- ducted two-sample MR analyses separately to estimate the causal effects of coagulation factors on endometrio - sis. To confirm the potential causal effects of coagulation factors, we further meta-analyzed endometriosis GWAS summary statistics from the UK Biobank and FinnGen. Finally, MR analyses were also performed to estimate the causal associations of coagulation factors with the risk of various sub-phenotypes of endometrioses, including endometriosis of the intestine, ovary, pelvic peritoneum, fallopian tube, uterus, rectovaginal septum, and vagina. Endometriosis GWAS summary statistics To obtain a reliable conclusion of the causal relation - ships between coagulation factors and the risk of endometriosis, we have conducted a systematic analy - sis of endometriosis GWAS summary-level data col - lected from two large-scale cohorts, including the UK Biobank and FinnGen. The GWAS summary statistics for endometriosis among individuals of European ancestry in the UK Biobank were procured from the Pan-UK Biobank website (https:// pan. ukbb. broad insti tute. org/) via a phenotype description search for “endo - metriosis” [25]. Correspondingly, the FinnGen cohort’s endometriosis GWAS summary statistics were accessi - ble via the R package TwoSampleMR (v 0.5.6) [26] using the GWAS ID “finn-b-N14_ENDOMETRIOSIS” as documented in the IEU OpenGWAS database (https:// gwas. mrcieu. ac. uk/) [27]. In the UK Biobank, the diagnosis of endometriosis was defined by N80 in the International Classification of Diseases, 10th Revision (ICD-10). The GWASs for endometriosis from the UK Biobank of European ancestry were conducted on 4354 cases and 217,500 female controls. In FinnGen, endo - metriosis is defined by N80 in ICD-10, 617 in ICD-9, and 6253 in ICD-8. The GWAS summary statistics for endometriosis from FinnGen included 8288 cases and 68,969 controls. In addition, we also curated summary- level GWAS data from the FinnGen cohort for various sub-phenotypes of endometrioses, including endome - triosis of the uterus (2372 cases, 68,969 controls), endo - metriosis of the ovary (3231 cases, 68,969 controls), endometriosis of the fallopian tube (116 cases, 68,969 controls), endometriosis of the pelvic peritoneum (2953 cases, 68,969 controls), endometriosis of the rectovagi - nal septum and vagina (1360 cases, 68,969 controls), and endometriosis of the intestine (177 cases, 68,969 controls). Fig. 1 Overall design of the MR analysis framework in this study. A flow chart depicts how the MR analysis was conducted step by step in this study Page 4 of 13Li et al. BMC Medicine (2023) 21:195 Genetic instrumental variable selection We used instrumental variables to investigate the causal associations between coagulation factors and endome - triosis. We searched for GWASs of coagulation factors in European populations to curate genetic variants associ - ated with coagulation factors. vWF, ADAMTS13, aPTT, FVII, FXI, FVII, FX, ETP , PAI-1, protein C, and plas - min were chosen as the examined coagulation factors with available genome-wide significant SNPs [28–36] (Additional file  1: Table  S1). Then, for each coagulation factor, we went through a stringent quality control pro - cedure to select eligible instrumental variables for each coagulation factor. First, we selected SNPs associated with specific coagulation factors at genome-wide signifi - cance (P < 5e − 7) as candidate instrumental variables for further MR analysis. Second, to ensure the instrumental variables for each exposure phenotype are independent, we used the linkage disequilibrium (LD)-based clumping to remove SNPs in strong LD (r 2 threshold = 0.1, window size = 10  Mb). The clumping step was carried out based on the European reference panel of the 1000 Genomes Project, which was used to estimate LD between SNPs. For SNPs that were not present in the endometriosis GWAS data, we used the LDlink tools to search for the most correlated proxy SNPs using the 1000 Genomes of European population data (r 2 > 0.8) [37]. We also dis - carded SNPs with non-concordant alleles and palin - dromic SNPs with ambiguous strands that could not be corrected when harmonizing the exposure data and out - come data. These stringently filtered SNPs were used as the instrumental variables for subsequent MR analyses. To determine whether there was a weak instrumental variable bias, we calculated F-statistics to quantify the strength of instrumental variables, where F-statistics larger than 10 indicates a low possibility of weak instru - mental variable bias [38, 39] (Additional file 1: Table S1). All the instrumental variable selection and quality con - trol steps are performed using the R package TwoSam - pleMR (v 0.5.6) [26]. Statistical power calculation We sought to assess the statistical power of our MR anal- yses through the use of an online web tool specialized for binary outcomes (https:// sb452. shiny apps. io/ power) [40]. The assessment of statistical power for MR analyses was based on several parameters, including the total sample size, the significance level of 0.05, the proportion of vari - ance (R2) in the exposure explained by instrumental vari - ables, and the ratio of cases to controls. Mendelian randomization estimates We combined the summary statistics (β coefficients and standard errors) to estimate the causal associations between 11 coagulation factors and endometriosis sepa - rately using different MR methods. The MR analyses were first performed separately in the UK Biobank and FinnGen cohorts. Three MR methods based on differ - ent assumptions were applied: inverse variance weighting (IVW), weighted mean (WM), and MR-Egger regres - sion. The IVW method was utilized as the main statis - tical model. There are fixed effects and random effects IVW methods available. We first calculated the causal estimates using the fixed effects IVW methods by meta- analyzing Wald ratio estimates for each instrumental var- iable. If significant heterogeneity (P < 0.05) is observed, the random effects IVW method is added. In addition, we also conducted MR analyses based on the meta-analyzed summary statistics which are combined from the UK Biobank and FinnGen using the METAL tool [41]. Causal estimates from MR analyses can only be inter - preted reliably if the three critical assumptions are met. Heterogeneity in causal estimates among instrumental variables indicates a potential violation of the assump - tions of MR analysis [42]. The Cochran’s Q test was used to examine the heterogeneity in causal estimates, and we used both the causal estimates of fixed effects IVW

Method

and MR-Egger regression to detect heterogene - ity. The heterogeneities were quantified using Cochran’s Q statistics and a P-value smaller than 0.05 was consid - ered significant heterogeneity. To assess the potential pleiotropic effects of instrumental variables, the MR- Egger regression was used. The directional horizontal pleiotropy in the causal estimates may be indicated by the intercept term in MR-Egger regression. Additionally, we performed a leave-one-out analysis where we excluded each SNP in turn and then ran MR analysis on the remaining SNPs in order to detect potentially outlying instrumental variables [26]. The Steiger test of direction - ality is also conducted to assess the causal relationship between the exposure and outcome. All MR analyses were performed using the R package TwoSampleMR (v 0.5.6) [26].

Results

Selection of instrumental variables We systematically curated genome-wide significant SNPs associated with 11 coagulation factors (vWF, ADAMTS13, aPTT, FVIII, FXI, FVII, FX, ETP , PAI-1, protein C, and plasmin) from different GWAS results through literature searching to examine the potential causal effects of these coagulation factors on the risk of endometriosis [28–36] (Additional file  1: Table S1). These coagulation factors could be categorized into five groups, including platelet adhesion (vWF and ADAMTS13), intrinsic pathway (FXI, aPTT, and FVIII), extrinsic path - way (FVII), common pathways (ETP and FX), and fibrin Page 5 of 13 Li et al. BMC Medicine (2023) 21:195 clot dissociation (PAI-1, protein C, and plasmin). We first kept the SNPs that were significantly associated with each exposure phenotype in the corresponding GWAS study (P < 5e − 7). Then, we used LD-based clumping to obtain the LD-independent SNPs for the exposure (r 2 threshold = 0.1, window size = 10  Mb). It is critical that the effect of an SNP on the exposure and the effect of that on the outcome are both attributed to the same allele. In the harmonizing process, ambiguous SNPs with non- concordant alleles and palindromic SNPs with ambigu - ous strands that cannot be corrected were discarded. Therefore, the number of SNPs chosen as instrumental variables for the exposure in subsequent two-sample MR analyses would eventually be equal to or less than that listed in Additional file  1: Table  S1. To assess the strength of each instrumental variable, we calculated the F-statistics for each instrument-exposure association. In our study, the F-statistics were much greater than 10, indicating that those SNPs were strong instrumental vari- ables (Additional file 1: Table S1). Moreover, we have cal- culated the statistical power for every exposure in each cohort. Notably, the results indicated that the statistical power ranged from 80% to 100% for all coagulation fac - tors, thereby affirming the robustness of our subsequent MR analyses (Additional file 1: Table S1). Causal effects of coagulation factors on endometriosis Based on the GWAS summary statistics for endome - triosis in the UK Biobank of European ancestry, which included 4354 cases and 217,500 controls, we performed MR analyses to estimate the causal effects of 11 coagu - lation factors on the risk of endometriosis. The MR estimates from different methods were shown in Addi - tional file 1: Table S2. The findings demonstrated that the genetically predicted plasma ADAMTS13 level is caus - ally associated with a decreased risk of endometriosis (IVW: OR = 0.37, 95%CI: 0.22–0.61, P = 1.25e − 4; WM: OR = 0.41, 95%CI: 0.23–0.72, P = 2.05e − 3) (Fig.  2A, Additional file  1: Table  S2, Additional file  2: Fig. S1). Notably, after accounting for multiple comparisons across 11 coagulation factors, the negative causal effects of plasma ADAMTS13 level on endometriosis remained significant (IVW: P adjusted = 1.38e − 3). Furthermore, we discovered a mild negative causal relationship between genetically predicted FXI levels and endometriosis (IVW: OR = 0.94, 95%CI: 0.89–0.98, P = 7.08e − 3; WM: OR = 0.95, 95%CI: 0.89–1.00, P = 0.059) (Fig.  2A, Addi - tional file  1: Table  S2, Additional file  2: Fig. S1). How - ever, other coagulation factors (vWF, aPTT, FVIII, FVII, FX, ETP , PAI-1, protein C, and plasmin) had no signifi - cant causal effect on endometriosis (Fig.  2A, Additional file 1: Table S2, Additional file  2: Fig. S1). Heterogeneity tests revealed heterogeneity in endometriosis for three coagulation factors, vWF (IVW: Cochran’s Q = 20.35, Phet- erogeneity = 0.041), aPTT (IVW: Cochran’s Q = 16.57, Phet- erogeneity = 0.011), and FVIII (IVW: Cochran’s Q = 11.80, Pheterogeneity = 0.003) (Additional file  1: Table  S2). Addi - tional MR analyses using the random effects IVW

Method

yielded causal effect estimates that were con - sistent with those estimated using the fixed effects IVW

Method

(Additional file  1: Table  S2). In the MR-Egger intercept test, we detected no significant evidence of horizontal pleiotropy (P pleiotropy > 0.05) (Additional file 1: Table  S2). Further leave-one-out analyses were carried out to ascertain potential outliers in the instrumen - tal variable estimation of ADATMS13 and FXI causal effects on the risk of endometriosis (Additional file  1: Table S3, Additional file  2: Fig. S2). Through the Steiger test of directionality, the results corroborated the nega - tive causal effects of ADAMTS13 and FXI on the risk of endometriosis (Additional file  1: Table S2). As a result of the MR analyses in the UK Biobank cohort, we were able to draw a robust conclusion that the genetically predicted plasma ADAMTS13 levels are causally associated with a decreased risk of endometriosis, and the association between FXI and the decreased risk of endometriosis is likely to be causal. As a replication analysis, we performed MR analyses based on the GWAS summary statistics for endometriosis in FinnGen (8288 cases and 68,969 controls). The findings highlighted that the negative causal effects of the geneti - cally predicted plasma ADAMTS13 level on the risk of endometriosis remained significant with a large effect size (IVW: OR = 0.46, 95%CI: 0.30–0.71, P = 5.31e − 4; WM: OR = 0.53, 95%CI: 0.33–0.85, P = 0.009), which was consistent with the findings from the UK Biobank (Fig. 2B, Additional file 1: Table S4, Additional file 2: Fig. S3). After multiple test correction, the causal association estimated using fixed effects IVW method remained sig - nificant (IVW: P adjusted = 5.8e − 3). Despite the presence of heterogeneity in the causal estimates for ADAMTS13 on endometriosis in FinnGen (IVW: Cochran’s Q = 11.91, Pheterogeneity = 0.003), the causal effects estimated using the random effects IVW method remained borderline signifi- cantly with a strong effect size (IVW: OR = 0.46, 95%CI: 0.16–0.1.34, P = 0.056) (Additional file  1: Table  S4). The

Results

also showed that the genetically predicted plasma vWF level was positively causally associated with the risk of endometriosis (IVW: OR = 1.28, 95%CI: 1.06–1.53, P = 0.009; WM: OR = 1.33, 95%CI: 1.08–1.62, P = 0.006), although the effect may not remain significant after adjusting for multiple comparisons (Fig.  2B, Additional file 1: Table S4, Additional file 2: Fig. S3). Conversely, the significant negative causal relationship between FXI and endometriosis observed in the UK Biobank was not rep - licated in FinnGen (Fig.  2B, Additional file  1: Table  S3, Page 6 of 13Li et al. BMC Medicine (2023) 21:195 Fig. 2 Causal estimates of 11 coagulation factors on endometriosis by MR analysis. A Forest plots showing causal estimates of 11 coagulation factors on endometriosis estimated in the UK Biobank of European ancestry. B Forest plots showing causal effects of 11 coagulation factors on endometriosis estimated in FinnGen. The odds ratio (OR) was estimated using the fixed effect IVW method. The horizontal bars represent 95% confidence intervals (CI) Page 7 of 13 Li et al. BMC Medicine (2023) 21:195 Additional file 2: Fig. S3). We observed no obvious hori - zontal pleiotropy in the MR-Egger intercept test and no potentially influential instrumental variable in the leave-one-out analysis for ADAMTS13 and vWF (Addi - tional file  1: Table  S4 and S5, Additional file  2: Fig. S4). The directionality of their causal effects was also con - firmed using the Steiger test (Additional file  1: Table S4). In conclusion, our FinnGen cohort results suggest that ADAMTS13 levels are causally associated with a decreased risk of endometriosis, and the positive associa - tion observed between vWF and the risk of endometrio - sis is likely to be causal. With the purpose of verifying the causal effects of coagulation factors on endometriosis, we meta-ana - lyzed the GWAS summary statistics obtained from the UK Biobank and FinnGen, thereby enhancing the sam - ple size and statistical power. Subsequent MR analy - ses were carried out using the meta-analyzed GWAS summary statistics for endometriosis. The results sup - ported the strong causal effect of ADAMTS13 on the decreased risk of endometriosis (IVW: OR = 0.42, 95%CI: 0.30–0.58, P = 2.85e − 7; WM: OR = 0.44, 95%CI: 0.30–0.66, P = 5.76e − 5) (Fig.  3, Additional file  1: Table S6, Additional file  2: Fig. S5). Notably, heteroge - neity in causal estimates of ADAMTS13 was detected by the heterogeneity test (IVW: Cochran’s Q = 13.23, Pheterogeneity = 0.004), necessitating use of the random effects IVW method to evaluate the causal association. The result from random effects IVW analysis confirmed the strong negative causal link between ADAMTS13 and endometriosis (Additional file  1: Table S6). The sig- nificant MR result of vWF on the risk of endometriosis was also observed (IVW: OR = 1.26, 95%CI: 1.09–1.46, P = 0.002; WM: OR = 1.29, 95%CI: 1.10–1.51, P = 0.002) (Fig.  3, Additional file  1: Table  S6, Additional file  2: Fig. S5). Moreover, the absence of potentially influen - tial instrumental variables was ascertained by leave- one-out analysis (Additional file  1: Table S7, Additional file  2: Fig. S6), and the Steiger test validated the direc - tionality of the causal effects on the risk of endome - triosis (Additional file  1: Table  S6). Summarizing the findings from the meta-analysis, we could conclude that the genetically predicted plasma ADAMTS13 levels have a negative causal effect on the risk of endometrio - sis, suggesting that ADAMTS13 serves as a protective factor for endometriosis. Conversely, the genetically predicted plasma vWF levels are positively associated with the risk of endometriosis, indicating vWF function as a risk factor for the development of endometriosis. Fig. 3 Causal estimates of 11 coagulation factors on endometriosis in a meta-analysis. Forest plots showing causal estimates of 11 coagulation factors on endometriosis in a meta-analysis of UK Biobank and FinnGen. The odds ratio (OR) was estimated using the fixed effect IVW method. The horizontal bars represent 95% confidence intervals (CI) Page 8 of 13Li et al. BMC Medicine (2023) 21:195 Causal effects of coagulation factors on different sub‑phenotypes of endometrioses Depending on the location and growth of ectopic endo - metriotic lesions, endometriosis could be categorized. The precise sub-phenotypes of endometriosis expe - rienced by patients may have an impact on both their symptoms as well as their chance of infertility. Endo - metrioses of the intestine, ovary, pelvic peritoneum, uterus, fallopian tube, and rectovaginal vaginal regions were among the five sub-phenotypes of endometrioses diagnosed in the FinnGen cohort. The GWAS summary statistics of various sub-phenotypes of endometrioses were also available in the FinnGen cohort. The number of patients ranged from 116 in endometriosis of the fal - lopian tube to 3231 in endometriosis of the ovary. Some patients might have more than one sub-phenotype of endometriosis because there was an overlap between dif - ferent sub-phenotypes. We employed MR analyses to further investigate the causal effects of genetically predicted plasma levels of ADAMTS13 and vWF on the risk of various sub-phe - notypes of endometrioses. The findings demonstrated that ADAMTS13 is negatively causally associated with the risk of endometriosis of the ovary (IVW: OR = 0.48, 95%CI: 0.25–0.92, P = 0.028; WM: OR = 0.58, 95%CI: 0.2–81.20, P = 0.140), endometriosis of the pelvic peri - toneum (IVW: OR = 0.32, 95%CI: 0.16–0.64, P = 0.001; WM: OR = 0.40, 95%CI: 0.19–0.85, P = 0.017), and endometriosis of the uterus (IVW: OR = 0.45, 95%CI: 0.21–0.97, P = 0.041; WM: OR = 0.44, 95%CI: 0.20–0.99, P = 0.048) (Fig. 4, Additional file 1: Table S8). In addition, ADAMTS13 had a negative but not statistically signifi - cant causal effect on endometriosis of the rectovaginal septum and vagina, and there was no evidence of a causal effect of ADAMTS13 on endometriosis of the intestine (Fig. 4, Additional file  1: Table S8). As heterogeneity was detected, we conducted a random effects IVW analysis to validate the findings (Additional file 1: Table S8). From the random effects IVW analysis, the causal estimates of ADAMTS13 on endometriosis of the uterus remained borderline significant (IVW: OR = 0.45, 95%CI: 0.20- –1.02, P = 0.051), while the causal estimates for endome - trioses of the ovary (IVW: OR = 0.48, 95%CI: 0.13–1.79, P = 0.274) and pelvic peritoneum (IVW: OR = 0.32, 95%CI:0.08–1.32, P = 0.116) attenuated towards non- significance (Additional file  1: Table S8). Meanwhile, the significant causal estimates of vWF were also observed for endometriosis of the ovary (IVW: OR = 1.34, 95%CI: Fig. 4 Causal estimates of vWF and ADAMTS13 on different sub-phenotypes of endometrioses. Forest plots depicting causal estimates of vWF and ADAMTS13 on different sub-phenotypes of endometrioses in FinnGen, including endometriosis of intestine, endometriosis of ovary, endometriosis of pelvic peritoneum, endometriosis of uterus, endometriosis of the fallopian tube, and endometriosis of the rectovaginal septum and vagina. The odds ratio (OR) was estimated using the fixed effect IVW method. The horizontal bars represent 95% confidence intervals (CI). Significant P values are highlighted in red Page 9 of 13 Li et al. BMC Medicine (2023) 21:195 1.02–1.77, P = 0.035; WM: OR = 1.37, 95%CI: 1.03–1.81, P = 0.028) and endometriosis of the pelvic peritoneum (IVW: OR = 1.48, 95%CI: 1.11–1.97, P = 0.008; WM: OR = 1.53, 95%CI: 1.13–2.08, P = 0.006) (Fig.  4, Addi - tional file 1: Table S8). In summary, the evidence suggests that ADAMTS13 may have a negative causal relationship with endometriosis of the ovary, pelvic peritoneum, and uterus, while vWF may have a positive causal relationship with endometriosis of the ovary and pelvic peritoneum. In addition, we noticed that the ratios of cases to con - trols significantly varied across sub-phenotypes, rang - ing from 1/594 for endometriosis of the fallopian tube to 1/21 for endometriosis of the ovary. Such disparity may impede the statistical power of a MR study, prompting the need to evaluate the statistical power. To establish the validity of the results, we additionally calculated the sta - tistical power for the MR analysis in each sub-phenotype cohort. The statistical power was merely about 14% and 20% for sub-phenotypes of the fallopian tube and intes - tine, respectively (Additional file  1: Table S8). Therefore, we should draw our conclusions with cautions for these two sub-phenotypes. In contrast, the statistical power for the other four sub-phenotypes, including endometriosis of the uterus, ovary, pelvic peritoneum, and rectovagi - nal septum and vagina ranged between 80% and 1, thus affirming the robustness of the MR results of these sub- phenotypes (Additional file 1: Table S8). In addition, the condition of endometriosis of the uterus, also referred to as adenomyosis, has been cat - egorized as a separate disease, despite its classification as a form of endometriosis in ICD-10. Several stud - ies have suggested that endometriosis and adenomyo - sis share similar pathophysiology, specifically related to somatic epithelial mutations and epigenetic abnormali - ties. In order to determine the potential effects of incor - porating endometriosis of the uterus in our MR study, we employed LDSC to examine the genetic correlations between adenomyosis and other sub-phenotypes [43, 44]. The results indicate strong genetic correlations, ranging from 0.67 to 0.93, indicating a shared genetic architec - ture and pathophysiological mechanisms between aden - omyosis and endometriosis (Additional file  1: Table S9). These findings suggest that the inclusion of adenomyosis is unlikely to significantly impact the causal estimation of coagulation factors on the risk of endometriosis.

Discussion

Utilizing summary statistics from two large-scale GWASs of European ancestry including UK Biobank and FinnGen, we investigated the causal effects of 11 coagulation factors on the risk of endometriosis, employ - ing a unified MR framework to analyze GWAS data. Our results indicate that genetically predicted plasma ADAMTS13 levels were inversely associated with endo - metriosis, while genetically predicted plasma vWF levels demonstrated a positive causal association with endo - metriosis, as confirmed in the meta-analysis combining the cohorts. Furthermore, MR analyses also revealed the causal associations in different sub-phenotypes of endo - metrioses that are categorized by ectopic location. These findings have significant implications for the develop - ment of endometriosis prevention strategies and treat - ment methods. For example, the findings underscore the significance of monitoring the ADAMTS13 plasma levels in individuals diagnosed with endometriosis. Fur - thermore, the results also provide a potential therapeutic approach that entails regulating the ADAMTS13 plasma level, thereby enabling the management and prevention of endometriosis progression and recurrence. Although several factors involved in the development of endometriosis have been uncovered, the precise etiol - ogy and pathogenesis of endometriosis remain obscure, and its treatment remains controversial [3, 4]. A thor - ough understanding of endometriosis is required for the development of effective preventative and treatment strategies. Sampson proposed the retrograde menstrua - tion theory, which states that menstrual blood contain - ing endometrial cells retrograde through fallopian tubes into the pelvic cavity instead of out of the body, leading to the formation of ectopic endometriotic lesions [45]. Although Sampson’s theory is the most widely accepted, several alternative hypotheses have been put forth, such as the theories of stem cell origin and altered immunity [46, 47]. Endometriosis is considered as a consequence of a complex interplay of genetic, anatomical, environ - mental, and immunologic factors [1–3]. Despite contra - dicting accounts regarding the origin of endometriosis, it is generally accepted that endometriosis is associated with a local inflammatory response, and that vasculariza - tion at the site of endometriotic invasion plays a crucial role in the development of the lesions [48]. Notably, the coagulation system has been acknowledged as playing critical roles in modulating both inflammatory responses and angiogenesis [12, 14–16]. Recently, Li et  al. have reported that the fibrinogen alpha chain could promote the migration and invasion of endometrial cells and promote angiogenesis in endometriosis [49–52]. Heavy menstrual bleeding (HMB) is a prevalent clinical symp - tom of endometriosis. Studies have raised the possibil - ity of an imbalance in coagulation factors playing a role in HMB in patients with endometriosis. Research has noted that women with endometriosis exhibit a hyperco - agulable status characterized by elevated levels of specific coagulation factors, such as fibrinogen and vWF [17–19, 53, 54]. These elevated factors may contribute to HMB by promoting the formation of blood clots. As such, an Page 10 of 13Li et al. BMC Medicine (2023) 21:195 imbalanced coagulation system may represent a plausi - ble etiologic mechanism behind HMB in endometriosis. Despite the growing interest regarding the involvement of coagulation factors in the pathogenesis of endometrio- sis, the causal roles of these factors in the development of endometriosis remain uncertain. This is the first study to investigate the causal relation - ships between coagulation factors and the risk of endo - metriosis utilizing MR analyses on large-scale population cohorts, which provided unconfounded causal estimates. The findings highlighted that the plasma ADAMTS13 levels have a negative causal effect on endometriosis, whereas the plasma vWF levels have a positive causal effect on endometriosis. In other words, ADAMTS13 is found to have a protective effect associated with endo - metriosis, while vWF is characterized as a risk factor for the development of the condition. The multimeric glycoprotein vWF is stored in the Weibel-Palade bodies and α-granules of platelets, awaiting release upon stim - ulation. Its primary function involves the formation of a bridge between surface receptors on platelets and the endothelium, allowing for platelet recruitment follow - ing an injury [55]. ADAMTS13 is a multidomain metal - loprotease that is predominantly synthesized in the liver by hepatic stellate cells, and its primary role is to regu - late thrombogenesis by cleaving hyperactive ultra-large multimers of vWFs into less active, smaller fragments [56]. Given the vWF-cleaving function of ADAMTS13, the biological functions of ADAMTS13 and vWF are closely related. The thrombotic thrombocytopenic pur - pua (TTP) that arises in people with severe ADAMTS13 deficiency has highlighted the relevance of ADAMTS13 function [57, 58]. ADAMTS13 deficiency may lead to the accumulation of vWF multimers, which causes intravas - cular platelet aggregation and microthrombosis, resulting in TTP . Aside from the well-established role in hemosta- sis, the balance between ADAMTS13 and vWF has been linked to a variety of diseases, such as systemic inflam - mation, pancreatitis, and multiple sclerosis [59–61]. The biosynthesis and secretion of ADAMTS13 from vascu - lar endothelial cells have raised the interests in the role of ADAMTS13 in angiogenesis [62–64]. The balance between ADAMTS13 and vWF is crucial for control - ling angiogenesis, as demonstrated by numerous studies [63]. In addition, Xiao et al. have recently demonstrated the proteolytically active ADAMTS13 is expressed in the human placental tissues and has a role in trophoblast cell proliferation, migration, invasion, and tube forma - tion [65]. Overall, the balance between ADAMTS13 and vWF not only regulates hemostasis, but also exerts a role in inflammation modulation, regulating angiogenesis, and tissue remodeling. Our findings of this MR study confirmed the causal roles of ADAMTS13 and vWF on endometriosis. Although the UK Biobank and FinnGen cohorts were utilized, there remains a need for independ- ent validation of these causal relationships. Furthermore, given the potential pathophysiology of endometriosis, a more comprehensive understanding of the molecular mechanisms and action of these coagulation factors in endometriosis pathogenesis requires additional experi - mental validation. There are several strengths in this study. First, because it is based on the fact that genetic variants are randomly allocated during gamete formation and conception, the

Results

of MR analysis are less susceptible to confounding bias and reverse causality [23]. Second, we employed sep- arate samples for the exposures (coagulation factors) and the outcome (endometriosis) data to ensure two-sam - ple MR analyses, which avoid inflating the bias of weak instrumental variables. Third, we incorporated two inde - pendent large-scale cohorts for MR analyses, followed by a meta-analysis, so that a sufficiently enough sample size of the outcome could assure the generalizability of causal associations. In addition, the consistent causal effect estimates of ADAMTS13 on endometriosis among the UK Biobank, FinnGen, and the meta-analysis alleviated concerns on false-positive results. Fourth, we employed multiple supplementary analyses, such as heterogeneity, pleiotropy, and leave-one-out sensitivity analyses, to ver - ify the viability of the assumptions regarding the instru - mental variables. Nonetheless, several limitations also need to be acknowledged. First, the number of instrumental vari - ables for each coagulation factor, as outlined in Addi - tional file  1: Table  S1 ranged from three to thirteen. Furthermore, some instrumental variables will be dis - carded during MR analyses when harmonizing the exposure and outcome data. These limitations suggest that the final MR estimates may be subject to influ - ence from the limited number of instrumental vari - ables. Nevertheless, the statistical power calculations for each coagulation factor within each cohort indicate that adequate power was achieved, with estimated sta - tistical power ranging from 80% to 1. Therefore, despite the potential limitations, the results presented in this study remain sufficiently powered to draw robust con - clusions. Second, only genome-wide significant SNPs for different coagulation factors were available in the exposure GWAS data, preventing us from perform - ing bi-directional MR analyses. Third, in the context of endometriosis, a female-specific condition, it is note - worthy that existing GWASs examining diverse coagu - lation factors have been conducted on a sex-combined bias. As two-sample MR necessitates consistency in the underlying population for both sample sets, it is impor - tant to consider potential discrepancies with regard Page 11 of 13 Li et al. BMC Medicine (2023) 21:195 to genetic estimates of coagulation factors in females versus males, which may introduce bias into our MR findings. Fourth, because this study was limited to peo - ple of European ancestry, the findings may not be gen - eralizable to other populations. More studies into the causal associations between coagulation factors and endometriosis in other populations are needed.

Conclusions

To the best of our knowledge, this is the first MR study to examine the causal associations between coagula - tion factors and the risk of endometriosis in the Euro - pean population. The findings convincingly support the causal associations between ADAMTS13/vWF and the risk of endometriosis. This study contributes to a bet - ter understanding of the involvement of coagulation cascades in the development of endometriosis. These findings may have important implications for endome - triosis prevention and treatment strategies. Abbreviations CI Confidence interval GWAS Genome-wide association study IVW Inverse variance weighting LD Linkage disequilibrium MR Mendelian randomization OR Odds ratio RCTs Randomized controlled trials SNP Single nucleotide polymorphism WM Weighted mean Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s12916- 023- 02881-z. Additional file 1: Table S1. Selected instrumental variables for coagula- tion factors in this study. Table S2. Summary statistics of the causal esti- mates of coagulation factors on endometriosis in UK Biobank. Table S3. The results of leave-one-out analyses for endometriosis in UK Biobank. Table S4. Summary statistics of the causal estimates of coagulation fac- tors on endometriosis in FinnGen. Table S5. The results of leave-one-out analyses for endometriosis in FinnGen. Table S6. Summary statistics of the causal estimates of coagulation factors on endometriosis in the meta- analysis. Table S7. The results of leave-one-out analyses for endometriosis in the meta-analysis. Table S8. Summary statistics of the causal estimates of vWF and ADAMTS13 on different sub-phenotypes of endometrioses. Table S9. Genetic correlations between endometriosis of uterus (adeno- myosis) and other sub-phenotypes. Additional file 2: Fig. S1. Scatter plots for MR analyses of the causal effect of 11 coagulation factors on endometriosis in UK Biobank. Fig. S2. Plots of leave-one-out analyses for the causal associations in UK Biobank. Fig. S3. Scatter plots for MR analyses of the causal effect of 11 coagulation factors on endometriosis in FinnGen. Fig. S4. Plots of leave-one-out analyses for the causal associations in FinnGen. Fig. S5. Scatter plots for MR analyses of the causal effect of ADAMTS13 and vWF on endometriosis in a meta-anal- ysis. Fig. S6. Plots of leave-one-out analyses for the causal associations in the meta-analysis.

Acknowledgements

We would like to thank the UK Biobank consortia, FinnGen consortia, GWAS Catalog, and Neale Lab for sharing the GWAS data. We would like to thank the anonymous reviewers for their constructive comments. Authors’ contributions YY, JW, and YD conceived and designed the study. YY supervised the study and data analysis. YL and HL performed the data analysis with help from SY, BZ, and XL. YY, JY, YL, and HL wrote the manuscript. All authors revised and approved the final manuscript. Funding This study was funded by the Natural Science Foundation of China (Grant No. 32100534 and No. 32200514), Talent Excellence Program from Tianjin Medical University (to YY). Availability of data and materials The GWAS summary statistics for coagulation factors are available in the GWAS Catalog or the published article and its supplementary files. The GWAS summary statistics for endometriosis are available on the Neale lab Pan-UK Biobank website (https:// pan. ukbb. broad insti tute. org/) for the UKBB cohort and the IEU GWAS database (https:// gwas. mrcieu. ac. uk/) for FinnGen [25, 27]. Declarations Ethics approval and consent to participate The analyses were based on publicly available data that have been approved by relevant review boards. The UK Biobank was approved by the Research Ethics Committee (REC reference: 21/NW/0157). The FinnGen was approved by the Coordinating Ethics Committee of the Hospital District of Helsinki and Uusimaa (HUS/990/2017). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1 Department of Family Planning, The Second Hospital of Tianjin Medical University, The Province and Ministry Co-Sponsored Collaborative Innova- tion Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tian- jin 300070, China. 2 State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosys- tems, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China. 3 Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medi- cal University, Tianjin 300070, China. Received: 20 January 2023 Accepted: 26 April 2023

References

1. Vercellini P , Vigano P , Somigliana E, Fedele L. Endometriosis: pathogenesis and treatment. Nat Rev Endocrinol. 2014;10(5):261–75. 2. Burney RO. The genetics and biochemistry of endometriosis. Curr Opin Obstet Gynecol. 2013;25(4):280–6. 3. Wang Y, Nicholes K, Shih IM. The origin and pathogenesis of endometrio- sis. Annu Rev Pathol. 2020;15:71–95. 4. Saunders PTK, Horne AW. Endometriosis: etiology, pathobiology, and therapeutic prospects. Cell. 2021;184(11):2807–24. 5. Vercellini P , Abbiati A, Vigano P , Somigliana ED, Daguati R, Meroni F, Cro- signani PG. Asymmetry in distribution of diaphragmatic endometriotic lesions: evidence in favour of the menstrual reflux theory. Hum Reprod. 2007;22(9):2359–67. Page 12 of 13Li et al. BMC Medicine (2023) 21:195 6. Christodoulakos G, Augoulea A, Lambrinoudaki I, Sioulas V, Creatsas G. Pathogenesis of endometriosis: the role of defective ‘immunosurveillance.’ Eur J Contracept Reprod Health Care. 2007;12(3):194–202. 7. Du Y, Liu X, Guo SW. Platelets impair natural killer cell reactivity and function in endometriosis through multiple mechanisms. Hum Reprod. 2017;32(4):794–810. 8. Yu JJ, Sun HT, Zhang ZF, Shi RX, Liu LB, Shang WQ, Wei CY, Chang KK, Shao J, Wang MY, et al. IL15 promotes growth and invasion of endometrial stromal cells and inhibits killing activity of NK cells in endometriosis. Reproduction. 2016;152(2):151–60. 9. Taylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic sys- temic disease: clinical challenges and novel innovations. Lancet. 2021;397(10276):839–52. 10. Othman Eel D, Hornung D, Salem HT, Khalifa EA, El-Metwally TH, Al-Hendy A. Serum cytokines as biomarkers for nonsurgical prediction of endome- triosis. Eur J Obstet Gynecol Reprod Biol. 2008;137(2):240–6. 11. Tseng JF, Ryan IP , Milam TD, Murai JT, Schriock ED, Landers DV, Taylor RN. Interleukin-6 secretion in vitro is up-regulated in ectopic and eutopic endometrial stromal cells from women with endometriosis. J Clin Endo- crinol Metab. 1996;81(3):1118–22. 12. May K, Becker CM. Endometriosis and angiogenesis. Minerva Ginecol. 2008;60(3):245–54. 13. Taylor RN, Yu J, Torres PB, Schickedanz AC, Park JK, Mueller MD, Sidell N. Mechanistic and therapeutic implications of angiogenesis in endometrio- sis. Reprod Sci. 2009;16(2):140–6. 14. Levi M, van der Poll T. Inflammation and coagulation. Crit Care Med. 2010;38(2 Suppl):S26-34. 15. Hess R, Wujak L, Hesse C, Sewald K, Jonigk D, Warnecke G, Fieguth HG, de Maat S, Maas C, Bonella F, et al. Coagulation factor XII regu- lates inflammatory responses in human lungs. Thromb Haemost. 2017;117(10):1896–907. 16. Belting M, Ahamed J, Ruf W. Signaling of the tissue factor coagulation pathway in angiogenesis and cancer. Arterioscler Thromb Vasc Biol. 2005;25(8):1545–50. 17. Vigano P , Ottolina J, Sarais V, Rebonato G, Somigliana E, Candiani M. Coagulation status in women with endometriosis. Reprod Sci. 2018;25(4):559–65. 18. Ottolina J, Bartiromo L, Dolci C, Salmeri N, Schimberni M, Villanacci R, Vigano P , Candiani M. Assessment of coagulation parameters in women affected by endometriosis: validation study and systematic review of the literature. Diagnostics (Basel). 2020;10(8):567. 19. Lin Q, Ding SJ, Zhu TH, Li TT, Huang XF, Zhang XM. Role and clinical signif- icance of coagulation and inflammatory factors in moderate and severe ovarian endometriosis. Zhonghua Fu Chan Ke Za Zhi. 2018;53(3):167–71. 20. Bulun SE, Yildiz S, Adli M, Chakravarti D, Parker JB, Milad M, Yang L, Chaudhari A, Tsai S, Wei JJ et al. Endometriosis and adenomyosis: shared pathophysiology. Fertil Steril. 2023;119(5):746–50. 21. Harmsen MJ, Wong CFC, Mijatovic V, Griffioen AW, Groenman F, Hehen- kamp WJK, Huirne JAF. Role of angiogenesis in adenomyosis-associated abnormal uterine bleeding and subfertility: a systematic review. Hum Reprod Update. 2019;25(5):647–71. 22. Grover S, Del Greco MF, Stein CM, Ziegler A. Mendelian randomization.

Methods

Mol Biol. 2017;1666:581–628. 23. Verduijn M, Siegerink B, Jager KJ, Zoccali C, Dekker FW. Mendelian ran- domization: use of genetics to enable causal inference in observational studies. Nephrol Dial Transplant. 2010;25(5):1394–8. 24. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisa- tion studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362: k601. 25. Pan-UK Biobank. Pan-ancestry genetic analysis of the UK Biobank. 2020. https:// pan. ukbb. broad insti tute. org. 26. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, et al. The MR-Base platform sup- ports systematic causal inference across the human phenome. Elife. 2018;7:e34408. 27. Elsworth B, Lyon M, Alexander T, Liu Y, Matthews P , Hallett J, Bates P , Palmer T, Haberland V, Smith GD, et al. The MRC IEU OpenGWAS data infrastructure. 2020. 28. Sabater-Lleal M, Huffman JE, de Vries PS, Marten J, Mastrangelo MA, Song C, Pankratz N, Ward-Caviness CK, Yanek LR, Trompet S, et al. Genome- wide association transethnic meta-analyses identifies novel associations regulating coagulation factor VIII and von Willebrand factor plasma levels. Circulation. 2019;139(5):620–35. 29. Ma Q, Jacobi PM, Emmer BT, Kretz CA, Ozel AB, McGee B, Kimchi-Sarfaty C, Ginsburg D, Li JZ, Desch KC. Genetic variants in ADAMTS13 as well as smoking are major determinants of plasma ADAMTS13 levels. Blood Adv. 2017;1(15):1037–46. 30. de Vries PS, Sabater-Lleal M, Huffman JE, Marten J, Song C, Pankratz N, Bartz TM, de Haan HG, Delgado GE, Eicher JD, et al. A genome-wide association study identifies new loci for factor VII and implicates factor VII in ischemic stroke etiology. Blood. 2019;133(9):967–77. 31. Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, Burgess S, Jiang T, Paige E, Surendran P , et al. Genomic atlas of the human plasma proteome. Nature. 2018;558(7708):73–9. 32. Rocanin-Arjo A, Cohen W, Carcaillon L, Frere C, Saut N, Letenneur L, Alhenc-Gelas M, Dupuy AM, Bertrand M, Alessi MC, et al. A meta-analysis of genome-wide association studies identifies ORM1 as a novel gene controlling thrombin generation potential. Blood. 2014;123(5):777–85. 33. Tang W, Basu S, Kong X, Pankow JS, Aleksic N, Tan A, Cushman M, Boer- winkle E, Folsom AR. Genome-wide association study identifies novel loci for plasma levels of protein C: the ARIC study. Blood. 2010;116(23):5032–6. 34. Tang W, Schwienbacher C, Lopez LM, Ben-Shlomo Y, Oudot-Mellakh T, Johnson AD, Samani NJ, Basu S, Gogele M, Davies G, et al. Genetic asso- ciations for activated partial thromboplastin time and prothrombin time, their gene expression profiles, and risk of coronary artery disease. Am J Hum Genet. 2012;91(1):152–62. 35. Suhre K, Arnold M, Bhagwat AM, Cotton RJ, Engelke R, Raffler J, Sarwath H, Thareja G, Wahl A, DeLisle RK, et al. Connecting genetic risk to disease end points through the human blood plasma proteome. Nat Commun. 2017;8:14357. 36. Huang J, Sabater-Lleal M, Asselbergs FW, Tregouet D, Shin SY, Ding J, Baumert J, Oudot-Mellakh T, Folkersen L, Johnson AD, et al. Genome- wide association study for circulating levels of PAI-1 provides novel insights into its regulation. Blood. 2012;120(24):4873–81. 37. Machiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics. 2015;31(21):3555–7. 38. Li B, Martin EB. An approximation to the F distribution using the chi- square distribution. Comput Stat Data Anal. 2002;40(1):21–6. 39. Georgakis MK, Gill D, Rannikmae K, Traylor M, Anderson CD, Lee JM, Kamatani Y, Hopewell JC, Worrall BB, Bernhagen J, et al. Genetically determined levels of circulating cytokines and risk of stroke. Circulation. 2019;139(2):256–68. 40. Burgess S. Sample size and power calculations in Mendelian randomi- zation with a single instrumental variable and a binary outcome. Int J Epidemiol. 2014;43(3):922–9. 41. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26(17):2190–1. 42. Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample sum- mary data Mendelian randomization. Stat Med. 2017;36(11):1783–802. 43. Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics C, Patterson N, Daly MJ, Price AL, Neale BM. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47(3):291–5. 44. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, ReproGen C, Psychiatric Genomics C, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control C, Dunca L, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47(11):1236–41. 45. Tsamantioti ES, Mahdy H. Endometriosis. In: StatPearls. edn. Treasure Island (FL); 2022. 46. Maruyama T. A revised stem cell theory for the pathogenesis of endome- triosis. J Pers Med. 2022;12(2):216. 47. Shigesi N, Kvaskoff M, Kirtley S, Feng Q, Fang H, Knight JC, Missmer SA, Rahmioglu N, Zondervan KT, Becker CM. The association between endometriosis and autoimmune diseases: a systematic review and meta- analysis. Hum Reprod Update. 2019;25(4):486–503. 48. Koninckx PR, Fernandes R, Ussia A, Schindler L, Wattiez A, Al-Suwaidi S, Amro B, Al-Maamari B, Hakim Z, Tahlak M. Pathogenesis based Page 13 of 13 Li et al. BMC Medicine (2023) 21:195 • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year • At BMC, research is always in progress. Learn more biomedcentral.com/submissions Ready to submit y our researc hReady to submit y our researc h ? Choose BMC and benefit fr om: ? Choose BMC and benefit fr om: diagnosis and treatment of endometriosis. Front Endocrinol (Lausanne). 2021;12:745548. 49. Li H, Cai E, Cheng H, Ye X, Ma R, Zhu H, Chang X. FGA controls VEGFA secretion to promote angiogenesis by activating the VEGFR2-FAK signal- ling pathway. Front Endocrinol (Lausanne). 2022;13:791860. 50. Zhao Y, Liu YN, Li Y, Tian L, Ye X, Cui H, Chang XH. Identification of bio- markers for endometriosis using clinical proteomics. Chin Med J (Engl). 2015;128(4):520–7. 51. Chen Y, Li H, Cheng HY, Rui-Qiong M, Ye X, Cui H, Hong-Lan Z, Chang XH. Fibrinogen alpha chain is up-regulated and affects the pathogenesis of endometriosis. Reprod Biomed Online. 2019;39(6):893–904. 52. Li H, Ma RQ, Cheng HY, Ye X, Zhu HL, Chang XH. Fibrinogen alpha chain promotes the migration and invasion of human endometrial stromal cells in endometriosis through focal adhesion kinase/protein kinase B/matrix metallopeptidase 2 pathway†. Biol Reprod. 2020;103(4):779–90. 53. Rizzello F, Ralli E, Romanelli C, Coccia ME. Severe recurrent endometrio- mas in a young woman with congenital von Willebrand disease. Gynecol Endocrinol. 2019;35(12):1040–2. 54. Yang B, Gu N, Shi S, Zhang C, Chen L, Ouyang J, Lin Y, Sun F, Xu H. Immu- noreactivity of plasminogen activator inhibitor 1 and its correlation with enomyosis. Reprod Sci. 2021;28(8):2378–86. 55. Bryckaert M, Rosa JP , Denis CV, Lenting PJ. Of von Willebrand factor and platelets. Cell Mol Life Sci. 2015;72(2):307–26. 56. Crawley JT, de Groot R, Xiang Y, Luken BM, Lane DA. Unraveling the scis- sile bond: how ADAMTS13 recognizes and cleaves von Willebrand factor. Blood. 2011;118(12):3212–21. 57. Warwicker P , Goodship JA, Goodship TH. von Willebrand factor-cleaving protease in thrombotic thrombocytopenic purpura and the hemolytic- uremic syndrome. N Engl J Med. 1999;340(17):1368–9. 58. Tsai HM, Lian EC. Antibodies to von Willebrand factor-cleaving pro- tease in acute thrombotic thrombocytopenic purpura. N Engl J Med. 1998;339(22):1585–94. 59. Reiter RA, Varadi K, Turecek PL, Jilma B, Knobl P . Changes in ADAMTS13 (von-Willebrand-factor-cleaving protease) activity after induced release of von Willebrand factor during acute systemic inflammation. Thromb Haemost. 2005;93(3):554–8. 60. Morioka C, Uemura M, Matsuyama T, Matsumoto M, Kato S, Ishikawa M, Ishizashi H, Fujimoto M, Sawai M, Yoshida M, et al. Plasma ADAMTS13 activity parallels the APACHE II score, reflecting an early prognostic indi- cator for patients with severe acute pancreatitis. Scand J Gastroenterol. 2008;43(11):1387–96. 61. Lu K, Liu L, Xu X, Zhao F, Deng J, Tang X, Wang X, Zhao BQ, Zhang X, Zhao Y. ADAMTS13 ameliorates inflammatory responses in experimental autoimmune encephalomyelitis. J Neuroinflammation. 2020;17(1):67. 62. Randi AM. Angiogenesis and the ADAMTS13-VWF balance. Blood. 2017;130(1):1–2. 63. Xu H, Cao Y, Yang X, Cai P , Kang L, Zhu X, Luo H, Lu L, Wei L, Bai X, et al. ADAMTS13 controls vascular remodeling by modifying VWF reactivity during stroke recovery. Blood. 2017;130(1):11–22. 64. Shang D, Zheng XW, Niiya M, Zheng XL. Apical sorting of ADAMTS13 in vascular endothelial cells and Madin-Darby canine kidney cells depends on the CUB domains and their association with lipid rafts. Blood. 2006;108(7):2207–15. 65. Xiao J, Feng Y, Li X, Li W, Fan L, Liu J, Zeng X, Chen K, Chen X, Zhou X, et al. Expression of ADAMTS13 in normal and abnormal placentae and its potential role in angiogenesis and placenta development. Arterioscler Thromb Vasc Biol. 2017;37(9):1748–56. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

⚙ Ask this paper AI returns verbatim quotes from the full text · source: oa-pdf ⓘ

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Condition tags

mesh:D004715endometriosisinfertility

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Blood Coagulation Blood Coagulation Blood Coagulation

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (64)

Cited by (50)

Source provenance

europepmc
last seen: 2026-06-04T01:30:01.192114+00:00
openalex
last seen: 2026-06-04T00:00:01.174412+00:00
pubmed
last seen: 2026-06-04T00:33:50.911596+00:00
License: CC0 · commercial use OK